2 citations · 2 across the 8 of their papers we have counts for
5 papers · 1 filter
SoK: You Find What You Seek: Rethinking Oracles, Guidance, and Input Generation in Hardware Fuzzing
G Abarajithan, Zhenghua Ma, Cristian Tirelli +4
Hardware fuzzing is an active area in security verification research, yet its industrial adoption remains in its early stages. This SoK examines which lessons from software fuzzing…
Reconfigurable Computing Challenge: Transformer for Jet Tagging on Versal AI Engines
Gram Koski, Sean Lipps, Zhenghua Ma +2
Transformer-based models achieve strong performance for jet tagging at the CERN LHC, but deploying them in low-latency, resource-constrained trigger systems is challenging. We pres…
Design Rules for Extreme-Edge Scientific Computing on AI Engines
Zhenghua Ma, G Abarajithan, Dimitrios Danopoulos +3
Extreme-edge scientific applications use machine learning models to analyze sensor data and make real-time decisions. Their stringent latency and throughput requirements demand sma…
FireBridge: Cycle-Accurate Hardware + Firmware Co-Verification for Modern Accelerators
G Abarajithan, Zhenghua Ma, Francesco Restuccia +1
Hardware-firmware integration is becoming a productivity bottleneck due to the increasing complexity of accelerators, characterized by intricate memory hierarchies and firmware-int…
Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)
Julia Gonski, Jennifer Ott, Jenni Ott +129
The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environmen…